The Transactions of The Korean Institute of Electrical Engineers (전기학회논문지)

The Korean Institute of Electrical Engineers (대한전기학회)
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A Study of Automatic Multi-Target Detection and Tracking Algorithm using Highest Probability Data Association in a Cluttered Environment

클러터가 존재하는 환경에서의 HPDA를 이용한 다중 표적 자동 탐지 및 추적 알고리듬 연구

  • 김다솔 (한양대학 공대 전자전기제어계측학과) ;
  • 송택렬 (한양대학 공대 전자전기제어계측학과)
  • Published : 2007.10.01
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Abstract

In this paper, we present a new approach for automatic detection and tracking for multiple targets. We combine a highest probability data association(HPDA) algorithm for target detection with a particle filter for multiple target tracking. The proposed approach evaluates the probabilities of one-to-one assignments of measurement-to-track and the measurement with the highest probability is selected to be target- originated, and the measurement is used for probabilistic weight update of particle filtering. The performance of the proposed algorithm for target tracking in clutter is compared with the existing clustering algorithm and the sequential monte carlo method for probability hypothesis density(SMC PHD) algorithm for multi-target detection and tracking. Computer simulation studies demonstrate that the HPDA algorithm is robust in performing automatic detection and tracking for multiple targets even though the environment is hostile in terms of high clutter density and low target detection probability.

Keywords

References

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